In this letter, we introduce a novel approach for lip activity detection and speaker detection, using solely visual information. The main idea in this work is to apply signal detection algorithms to a simple and easily extracted feature from the mouth region. We argue that the increased average value and standard deviation of the number of pixels with low intensities that the mouth region of a speaking person demonstrates can be used as visual cues for detecting visual speech. We then proceed in deriving a statistical algorithm that utilizes this fact for the efficient characterization of visual speech and silence in video sequences. Furthermore, we employ the lip activity detection method in order to determine the active speaker(s) in a multi-person environment.Index Terms-Speaker detection, visual speech detection.

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This paper presents a new approach for the segmentation of color textured images, which is based on a novel energy function. The proposed energy function, which expresses the local smoothness of an image area, is derived by exploiting an intermediate step of modal analysis that is utilized in order to describe and analyze the deformations of a 3-D deformable surface model. The external forces that attract the 3-D deformable surface model combine the intensity of the image pixels with the spatial information of local image regions. The proposed image segmentation algorithm has two steps. First, a color quantization scheme, which is based on the node displacements of the deformable surface model, is utilized in order to decrease the number of colors in the image. Then, the proposed energy function is used as a criterion for a region growing algorithm. The final segmentation of the image is derived by a region merge approach. The proposed method was applied to the Berkeley segmentation database. The obtained results show good segmentation robustness, when compared to other state of the art image segmentation algorithms.

This paper presents an audio-visual database that can be used as a reference database for testing and evaluation of video, audio or joint audio-visual person tracking algorithms, as well as speaker localization methods. Additional possible uses include the testing of face detection and pose estimation algorithms. A number of different scenes are included in the database, ranging from simple to complex scenes that can challenge existing algorithms. They include different subjects, with appearances that can cause problems to video tracking algorithms, (e.g. facial features such as beards, glasses, etc.), optimal and artificially created sub-optimal lighting conditions, subject movement based on simple as well as random motion trajectories, different distances from the camera/microphones and occlusion. The database incorporates ground truth data (3-D position in time) originating from a commercially available 4-camera infrared (IR) tracking system. Examples of how the database can be used to evaluate video and audio tracking algorithms are also provided.

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This paper presents a complete functional system capable of detecting people and tracking their motion in either live camera feed or pre-recorded video sequences. The system consists of two main modules, namely the detection and tracking modules. Automatic detection aims at locating human faces and is based on fusion of color and feature-based information. Thus, it is capable of handling faces in different orientations and poses (frontal, profile, intermediate). To avoid false detections, a number of decision criteria are employed. Tracking is performed using a variant of the well-known Kanade-Lucas-Tomasi tracker, while occlusion is handled through a re-detection stage. Manual intervention is allowed to assist both modules if required. In manual mode, the system can track any object of interest, so long as there are enough features to track. The system caters for calibrated cameras and can provide 3-D coordinates of any tracked object(s) of interest. It has been tested with very good results on a variety of video sequences, including a database of studio video sequences, for which 3-D ground truth data, originating from a 4-camera infrared tracking system, exist.

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